





import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


snake_case_           =     logging.get_logger(__name__)

snake_case_           =     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case_           =     {
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/tokenizer.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/tokenizer.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json',
        'roberta-base-openai-detector': (
            'https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'
        ),
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'
        ),
    },
}

snake_case_           =     {
    'roberta-base': 512,
    'roberta-large': 512,
    'roberta-large-mnli': 512,
    'distilroberta-base': 512,
    'roberta-base-openai-detector': 512,
    'roberta-large-openai-detector': 512,
}

class 						SCREAMING_SNAKE_CASE__							(			_UpperCAmelCase    ):
      A_		:							Tuple				=       VOCAB_FILES_NAMES
      A_		:							Dict				=       PRETRAINED_VOCAB_FILES_MAP
      A_		:							Optional[int]				=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A_		:							List[Any]				=       ['input_ids', 'attention_mask']
      A_		:							List[Any]				=       RobertaTokenizer


      def __init__(self			: List[Any]							,     a__			: Optional[Any]=None							,     a__			: Optional[Any]=None							,     a__			: Optional[Any]=None							,     a__			: List[str]="replace"							,     a__			: Optional[Any]="<s>"							,     a__			: int="</s>"							,     a__			: Dict="</s>"							,     a__			: Optional[Any]="<s>"							,     a__			: Any="<unk>"							,     a__			: Tuple="<pad>"							,     a__			: Dict="<mask>"							,     a__			: int=False							,     a__			: List[Any]=True							,     **a__			: Optional[int]							,     ):





         """simple docstring"""



         super().__init__(
             lowercase_							,     lowercase_							,     tokenizer_file=lowercase_							,     errors=lowercase_							,     bos_token=lowercase_							,     eos_token=lowercase_							,     sep_token=lowercase_							,     cls_token=lowercase_							,     unk_token=lowercase_							,     pad_token=lowercase_							,     mask_token=lowercase_							,     add_prefix_space=lowercase_							,     trim_offsets=lowercase_							,     **lowercase_							,     )

         __snake_case							=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
         if pre_tok_state.get('''add_prefix_space'''							,     lowercase_ ) != add_prefix_space:
            __snake_case							=  getattr(lowercase_							,     pre_tok_state.pop('''type''' ) )
            __snake_case							=  add_prefix_space
            __snake_case							=  pre_tok_class(**lowercase_ )

         __snake_case							=  add_prefix_space

         __snake_case							=  '''post_processor'''
         __snake_case							=  getattr(self.backend_tokenizer							,     lowercase_							,     lowercase_ )
         if tokenizer_component_instance:
            __snake_case							=  json.loads(tokenizer_component_instance.__getstate__() )

            # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
            if "sep" in state:
               __snake_case							=  tuple(state['''sep'''] )
            if "cls" in state:
               __snake_case							=  tuple(state['''cls'''] )

            __snake_case							=  False

            if state.get('''add_prefix_space'''							,     lowercase_ ) != add_prefix_space:
               __snake_case							=  add_prefix_space
               __snake_case							=  True

            if state.get('''trim_offsets'''							,     lowercase_ ) != trim_offsets:
               __snake_case							=  trim_offsets
               __snake_case							=  True

            if changes_to_apply:
               __snake_case							=  getattr(lowercase_							,     state.pop('''type''' ) )
               __snake_case							=  component_class(**lowercase_ )
               setattr(self.backend_tokenizer							,     lowercase_							,     lowercase_ )


      @property
      def   a					(self			: int ):





         """simple docstring"""



         if self._mask_token is None:
            if self.verbose:
               logger.error('''Using mask_token, but it is not set yet.''' )
            return None
         return str(self._mask_token )


      @mask_token.setter
      def   a					(self			: List[Any]							,     a__			: Optional[Any] ):





         """simple docstring"""



         __snake_case							=  AddedToken(lowercase_							,     lstrip=lowercase_							,     rstrip=lowercase_ ) if isinstance(lowercase_							,     lowercase_ ) else value
         __snake_case							=  value


      def   a					(self			: Optional[int]							,     *a__			: List[str]							,     **a__			: int ):





         """simple docstring"""



         __snake_case							=  kwargs.get('''is_split_into_words'''							,     lowercase_ )
         assert self.add_prefix_space or not is_split_into_words, (
             f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
             "to use it with pretokenized inputs."
         )

         return super()._batch_encode_plus(*lowercase_							,     **lowercase_ )


      def   a					(self			: str							,     *a__			: Optional[int]							,     **a__			: Dict ):





         """simple docstring"""



         __snake_case							=  kwargs.get('''is_split_into_words'''							,     lowercase_ )

         assert self.add_prefix_space or not is_split_into_words, (
             f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
             "to use it with pretokenized inputs."
         )

         return super()._encode_plus(*lowercase_							,     **lowercase_ )


      def   a					(self			: str							,     a__			: str							,     a__			: Optional[str] = None ):





         """simple docstring"""



         __snake_case							=  self._tokenizer.model.save(lowercase_							,     name=lowercase_ )
         return tuple(lowercase_ )


      def   a					(self			: Dict							,     a__			: Dict							,     a__			: str=None ):





         """simple docstring"""



         __snake_case							=  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
            return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]


      def   a					(self			: List[str]							,     a__			: List[int]							,     a__			: Optional[List[int]] = None ):





         """simple docstring"""



         __snake_case							=  [self.sep_token_id]
         __snake_case							=  [self.cls_token_id]

         if token_ids_a is None:
            return len(cls + token_ids_a + sep ) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]


from math import isqrt, loga


def 				lowerCAmelCase__       (			a__ )      ->list[int]:




  '''simple docstring'''

  _UpperCamelCase           =    [True] * max_number
  for i in range(2    ,     isqrt(max_number - 1 ) + 1 ):
    if is_prime[i]:
      for j in range(i**2    ,     a__    ,     a__ ):
        _UpperCamelCase           =    False

  return [i for i in range(2    ,     a__ ) if is_prime[i]]


def 				lowerCAmelCase__       (			a__ = 800_800    ,     a__ = 800_800 )      ->int:




  '''simple docstring'''

  _UpperCamelCase           =    degree * loga(a__ )
  _UpperCamelCase           =    int(a__ )
  _UpperCamelCase           =    calculate_prime_numbers(a__ )

  _UpperCamelCase           =    0
  _UpperCamelCase           =    0
  _UpperCamelCase           =    len(a__ ) - 1
  while left < right:
    while (
        prime_numbers[right] * loga(prime_numbers[left] )
        + prime_numbers[left] * loga(prime_numbers[right] )
        > upper_bound
    ):
      right -= 1
    hybrid_integers_count += right - left
    left += 1

  return hybrid_integers_count


if __name__ == "__main__":
   print(F"{solution() = }")




